- Open Access
- Article
Product in Product Type Estimator with Exponential and Log Function to Estimate Population Mean Using DSS
by Sangeeta Malik , Rubal Sharma
and Ruchi Gupta
Baba Mastnath University Asthal Bohar Rohtak,Haryana, Department of Mathematics, 124021, India
* Author to whom correspondence should be addressed.
Journal of Engineering Research and Sciences, Volume 4, Issue 2, Page # 11-17, 2025; DOI: 10.55708/js0402002
Keywords: Finite population mean, Bias, Mean Squared Error, Double sampling for stratification (DSS
Received: 14 January 2025, Revised: 05 February 2025, Accepted: 06 February 2025, Published Online: 11 February 2025
(This article belongs to the Special Issue Special Issue on Multidisciplinary Sciences and Advanced Technology 2024 & Section Biochemical Research Methods (BRM))
APA Style
Sharma, R., Malik, S., & Gupta, R. (2025). Product in product type estimator with exponential and log function to estimate population mean using DSS. Journal of Engineering Research and Sciences, 4(2), 11–17. https://doi.org/10.55708/js0402002
Chicago/Turabian Style
Sharma, Rubal, Sangeeta Malik, and Ruchi Gupta. “Product in Product Type Estimator with Exponential and Log Function to Estimate Population Mean Using DSS.” Journal of Engineering Research and Sciences 4, no. 2 (2025): 11–17. https://doi.org/10.55708/js0402002.
IEEE Style
R. Sharma, S. Malik, and R. Gupta, “Product in Product Type Estimator with Exponential and Log Function to Estimate Population Mean Using DSS,” Journal of Engineering Research and Sciences, vol. 4, no. 2, pp. 11–17, 2025, doi: 10.55708/js0402002.
To estimate the population, mean in two-phase stratified sampling, this paper aims to construct a new product in the product type estimator using exponential and log functions. When using two samples for stratification, this study attempts to solve the equation for bias and mean squared error (MSE) up to the first degree of approximation (fda). The modified estimator is more effective than y‾ds (the usual unbiased estimator,Y‾ˆ PPds(Ige & Tripathi ratio estimator) and YˆPPe (ratio type exponential estimator) given by Tailor et al. theoretically and numerically. Finding out how the proposed estimators stack up against the state-of-the-art is the main motivation for this research. Extensive evaluation of the estimator’s performance in a simulated environment. The suggested estimators perform better than other estimators, according to both theoretical and practical studies.
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